comparison of the psychological skills of Iranian and world male fencers
Bibliographic record
Abstract
Introduction: Recently, the matter of the influence of mental skills on sports skills performance has become very important. The current research aimed to evaluate and compare the mental preparation of the male fencers of the Iranian national team and the elite male fencers of the world.Methods: The current research method was experimental. The statistical population of this research included the fencers of the national teams of Iran, Hungary, America, Russia, France, and Ukraine. The research samples were 58 fencers from selected countries. To measure the mental skills of fencers, the original version of the Ottawa Mental Skills Assessment Tool (OMSAT-3) questionnaire was used. To compare the mental skills of athletes from different countries, the Multivariate Analysis of Variance (MANOVA) and Bonferroni's post hoc test were used.Results: The results showed that all elite male fencers achieved the highest scores in foundation mental skills including self-confidence, goal setting, and commitment, and the lowest scores were related to refocusing, focusing, and stress control skills. Also, the highest and the lowest scores of mental skills in this research were related to self-confidence and refocusing skills, respectively. Russian fencers scored the highest in all mental skills and Iranian fencers scored the lowest in the stress control skill.Conclusion: Based on the results of the research, fencers have less proficiency in two sub-skills of cognitive psychological and psychosomatic skills compared with the foundation mental skills. The fencers had lower strength in terms of the mental skill of focusing, refocusing, and stress control. Iranian and non-Iranian fencers were weaker in mental skills of stress control and refocusing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".